Perceptions as Hypotheses: Saccades as Experiments

By Karl J. Friston, Rick A Adams, Laurent Udo Perrinet, Michael Breakspear. Front. Psychology, 2012

424 citations recorded by the source corpus.

If perception corresponds to hypothesis testing (Gregory, 1980); then visual searches might be construed as experiments that generate sensory data. In this work, we explore the idea that saccadic eye movements are optimal experiments, in which data are gathered to test hypotheses or beliefs about how those data are caused. This provides a plausible model of visual search that can be motivated from the basic principles of self-organized behavior: namely, the imperative to minimize the entropy of hidden states of the world and their sensory consequences. This imperative is met if agents sample hidden states of the world efficiently. This efficient sampling of salient information can be derived in a fairly straightforward way, using approximate Bayesian inference and variational free-energy minimization. Simulations of the resulting active inference scheme reproduce sequential eye movements that are reminiscent of empirically observed saccades and provide some counterintuitive insights into the way that sensory evidence is accumulated or assimilated into beliefs about the world.

Subfields: Cognitive Neuroscience, Sensory Systems

View Paper: https://www.semanticscholar.org/paper/04bc5da3f1e62a68f03692182ac4fededf9d1518

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Citations in the corpus

Active inference and epistemic value (2015, methodology): “We have previously considered epistemic value and salience using continuous time predictive coding schemes and saccadic searches (Friston et al., 2012).”
Self-organization of early vocal development in infants and machines: the role of intrinsic motivation (2014, background): “Learning progress refers to the infant’s improvement of his predictions or control over activity they practice, which can also be described as reduction of uncertainty (Friston et al., 2012).”
The graphical brain: Belief propagation and active inference (2017, methodology): “In this paper, we focus on the integration of a Markov decision process model of visual search (Mirza et al., 2016) with a predictive coding model of saccadic eye movements (K. Friston et al., 2012), to produce a complete (mixed) model of evidence accumulation.”
How Evolution May Work Through Curiosity-Driven Developmental Process (2016, methodology): “Information seeking mechanisms have been used either as an “exploration bonus” mechanism in service of efficient maximization of a task-specific reward, or as primary rewards driving models of curiosity-driven learning (Gottlieb et al., 2013).”
Criticality in the brain: A synthesis of neurobiology, models and cognition. (2017, background): “Computational models also show that neural systems have maximum adaptability to accommodate incoming processing demands when they are close to a critical point (Friston et al., 2012b; Friston, 2000; Gollo and Breakspear, 2014; Kastner et al., 2015; Shew et al., 2009; Yang et al., 2012).”
From cognitivism to autopoiesis: towards a computational framework for the embodied mind (2016, background): “…(Chemero 2011), FEP renders a productive union of the embodied cognition and information theory, allowing the enactivist not only to describe the importance of the body, but to also build models of the brain-body-world relationship (See Friston et al. 2012a,b for one illustrative example).”
Vanilla PP for Philosophers: A Primer on Predictive Processing (2017, background): “(Von Helmholtz 1959[1879/1887], p. 39)20 A classical application in the present debate is saccadic eye movements, which are now conceptualized as an embodied form of hypothesis-testing (Friston et al. 2012b).”
A nice surprise? Predictive processing and the active pursuit of novelty (2018, methodology): “Notice, however, that action also provides a potent means of testing the current hypothesis, for example disambiguating between equiprobable hypotheses (Seth (2015), Friston et al. (2012a)).”
The free energy principle made simpler but not too simple (2022, neutral): “Please see [162] for further details. one can mix discrete and continuous state–space models by placing the former on top of the latter, to produce deep generative models that, through active inference, can be used to simulate many known aspects of computational anatomy and physiology in the brain…”
A free energy principle for a particular physics (2019, methodology): “This is why we have previously asserted that the agent is (or entails) a generative model of its world – as opposed to possessing a generative model (Friston, 2013).”
Busting Out: Predictive Brains, Embodied Minds, and the Puzzle of the Evidentiary Veil (2017, background): “Contextually recruited patterns of precision weighting thus accomplish a form of set-selection or strategy switching – an effect that has been practically demonstrated in some simple simulations of cued reaching (K. J. Friston et al., 2012)).”
Navigating the Affordance Landscape: Feedback Control as a Process Model of Behavior and Cognition. (2016, neutral): “Third, active perception refers to strategies of sensor or eye movement control that permit, for example, to implement the right stimuli for the current action context [73] or hypothesis testing [74].”
Life as we know it (2013, neutral): “If one pursues this in a neuroscience setting, one arrives at a compelling explanation for the way we adaptively sample our environments—to minimize uncertainty about the causes of sensory inputs [62].”